July 2022 arXiv papers — page 8

Sijin Long, Long Chen, Yuxin Wang, Ying Zhou

One of the universal features of unconventional superconductors is that the superconducting (SC) state is developed in the proximity of an antiferromagnetic (AFM) state. Understanding the interplay between these two states is one of the key issues to uncover the underlying physics of unconventional SC mechanism. Here, we report a pressure-induced flipping of

Yuxin Ma, Ping Gong, Jun Yi, Zhewei Yao

Graph Neural Networks (GNNs) is a promising approach for applications with nonEuclidean data. However, training GNNs on large scale graphs with hundreds of millions nodes is both resource and time consuming. Different from DNNs, GNNs usually have larger memory footprints, and thus the GPU memory capacity and PCIe bandwidth are the main resource bottlenecks i

Alemiye M. Yacob, Leonid N. Berdnikov, Elena N. Pastukhova, Alexei Y. Kniazev

In this study, we investigate the period changes of eight short-period Type II Cepheids of the BL Her subtype, i.e., with periods in the 1-4 day range. The $O-C$ diagrams for these stars are constructed using all suitable observational data from ground and space surveys. This spans a time interval of over one century and includes digitized photographic plate

Michael Yuhas, Daniel Jun Xian Ng, Arvind Easwaran

When machine learning (ML) models are supplied with data outside their training distribution, they are more likely to make inaccurate predictions; in a cyber-physical system (CPS), this could lead to catastrophic system failure. To mitigate this risk, an out-of-distribution (OOD) detector can run in parallel with an ML model and flag inputs that could lead t

Antoine Huchet, Jean-Loup Guillaume, Yacine Ghamri-Doudane

To study the propagation of information from individual to individual, we need mobility datasets. Existing datasets are not satisfactory because they are too small, inaccurate or target a homogeneous subset of population. To draw valid conclusions, we need sufficiently large and heterogeneous datasets. Thus we aim for a passive non-intrusive data collection

Filiberto Ares, Sara Murciano, Pasquale Calabrese

Symmetry and symmetry breaking are two pillars of modern quantum physics. Still, quantifying how much a symmetry is broken is an issue that has received little attention. In extended quantum systems, this problem is intrinsically bound to the subsystem of interest. Hence, in this work, we borrow methods from the theory of entanglement in many-body quantum sy

Christopher Blier-Wong, Hélène Cossette, Etienne Marceau

We offer a new perspective on risk aggregation with FGM copulas. Along the way, we discover new results and revisit existing ones, providing simpler formulas than one can find in the existing literature. This paper builds on two novel representations of FGM copulas based on symmetric multivariate Bernoulli distributions and order statistics. First, we detail

Ignacio Vergara

We show that every hyperbolic group has a proper uniformly Lipschitz affine action on a subspace of an $L^1$ space. We also prove that every acylindrically hyperbolic group has a uniformly Lipschitz affine action on such a space with unbounded orbits. Our main tools are the $\mathbb{Q}$-bicombings on hyperbolic groups constructed by Mineyev and the character

Aadesh Madnaik, Sharayu Moharir, Nikhil Karamchandani

We consider the setting where a service is hosted on a third-party edge server deployed close to the users and a cloud server at a greater distance from the users. Due to the proximity of the edge servers to the users, requests can be served at the edge with low latency. However, as the computation resources at the edge are limited, some requests must be rou

Taira Oogi, Tomoaki Ishiyama, Francisco Prada, Manodeep Sinha

Measurements of the luminosity function of active galactic nuclei (AGN) at high redshift ($z\gtrsim 6$) are expected to suffer from field-to-field variance, including cosmic and Poisson variances. Future surveys, such as those from the Euclid telescope and James Webb Space Telescope (JWST), will also be affected by field variance. We use the Uchuu simulation

Denise Moussa, Anatol Maier, Andreas Spruck, Jürgen Seiler

Forensic license plate recognition (FLPR) remains an open challenge in legal contexts such as criminal investigations, where unreadable license plates (LPs) need to be deciphered from highly compressed and/or low resolution footage, e.g., from surveillance cameras. In this work, we propose a side-informed Transformer architecture that embeds knowledge on the

Eric T. Sawyer, Brett D. Wick

We prove a T1 theorem for fractional vector Riesz transforms mapping one weighted Sobolev space to another, where the weights are doubling measures on Euclidean space. Boundedness is characterized by the classical A_2 condition and two dual testing conditions on indicators of cubes. We also show the equivalence of various weighted Sobolev norms when the meas

Mariaveronica De Angelis, Giovanni Montani

We demonstrate a spontaneous tendency of quantum wave packets to become quasi-classical, providing a classical limit for the Universe dynamics. However, this limit is not maintained in the future (after a critical value of the relational time) and a spreading process is turned on. We show that the onset of an inflationary scenario is not able to make this lo

Denise Moussa, Germans Hirsch, Christian Riess

Freely available and easy-to-use audio editing tools make it straightforward to perform audio splicing. Convincing forgeries can be created by combining various speech samples from the same person. Detection of such splices is important both in the public sector when considering misinformation, and in a legal context to verify the integrity of evidence. Unfo

David Leimstädtner, Peter Sörries, Claudia Müller-Birn

Routinely collected clinical patient data posits a valuable resource for data-driven medical innovation. Such secondary data use for medical research purposes is dependent on the patient's consent. To gain an understanding of the patients' values and needs regarding medical data donations, we developed a participatory workshop method, integrating approaches

Lars Eric Hientzsch, Christophe Lacave, Evelyne Miot

The global asymptotic dynamics of point vortices for the lake equations is rigorously derived. Vorticity that is initially sharply concentrated around $N$ distinct vortex centers is proven to remain concentrated for all times. Specifically, we prove weak concentration of the vorticity and in addition strong concentration in the direction of the steepest asce

Rachel Baïle, Jean-François Muzy

In this paper, we address the issue of short-term wind speed prediction at a given site. We show that, when one uses spatiotemporal information as provided by wind data of neighboring stations, one significantly improves the prediction quality. Our methodology does not focus on any peculiar forecasting model but rather considers a set of various prediction m

Yibo Shi, Yunying Ge, Jing Wang, Jue Mao

Recently, learned video compression has drawn lots of attention and show a rapid development trend with promising results. However, the previous works still suffer from some criticial issues and have a performance gap with traditional compression standards in terms of widely used PSNR metric. In this paper, we propose several techniques to effectively improv

Ozioma Collins Oguine, Kanyifeechukwu Jane Oguine, Hashim Ibrahim Bisallah

The term Big Data has been coined to refer to the gargantuan bulk of data that cannot be dealt with by traditional data-handling techniques. Big Data is still a novel concept, and in the following literature, we intend to elaborate on it in a palpable fashion. It commences with the concept of the subject in itself, along with its properties and the two gener

Tim Lebailly, Tinne Tuytelaars

The downstream accuracy of self-supervised methods is tightly linked to the proxy task solved during training and the quality of the gradients extracted from it. Richer and more meaningful gradients updates are key to allow self-supervised methods to learn better and in a more efficient manner. In a typical self-distillation framework, the representation of

Dimitra Atri, Margaret Kamenetskiy, Michael May, Archit Kalra

Ionizing radiation is known to have a destructive effect on biology by causing damage to the DNA, cells, and production of Reactive Oxygen Species (ROS), among other things. While direct exposure to high radiation dose is indeed not favorable for biological activity, ionizing radiation can, and in some cases is known to produce a number of biologically usefu

Matthew McDermott, Jason Rife

Lidar data can be used to generate point clouds for the navigation of autonomous vehicles or mobile robotics platforms. Scan matching, the process of estimating the rigid transformation that best aligns two point clouds, is the basis for lidar odometry, a form of dead reckoning. Lidar odometry is particularly useful when absolute sensors, like GPS, are not a

Rémi Granger, Luc Salvo, Sabine Rolland du Roscoat, Pierre Lhuissier

Photon Counting Detectors (PCDs) open new opportunities in X-ray imaging. Pixie III is a PCD using simultaneously two energy thresholds. This enables to acquire images using two distinct energy bins in a single exposure and allows to perform K-Edge Subtraction (KES) imaging with laboratory sources. In that context, one has however to deal with an energy bin

David Bartl, Miklós Pintér

We consider transferable utility cooperative games with infinitely many players and the core understood in the space of bounded additive set functions. We show that, if a game is bounded below, then its core is non-empty if and only if the game is balanced. This finding is a generalization of Schmeidler's (1967) original result ``On Balanced Games with Infin

Bruno Lecouat, Thomas Eboli, Jean Ponce, Julien Mairal

Photographs captured by smartphones and mid-range cameras have limited spatial resolution and dynamic range, with noisy response in underexposed regions and color artefacts in saturated areas. This paper introduces the first approach (to the best of our knowledge) to the reconstruction of high-resolution, high-dynamic range color images from raw photographic

Fabio Müller, Henrik Christiansen, Stefan Schnabel, Wolfhard Janke

We present a fast, hierarchical, and adaptive algorithm for Metropolis Monte Carlo simulations of systems with long-range interactions that reproduces the dynamics of a standard implementation exactly, i.e., the generated configurations and consequently all measured observables are identical, allowing in particular for nonequilibrium studies. The method is d

A. Latorre, L. Ugarte, R. Villacampa

In this paper we focus on the interplay between the behaviour of the Fr\"olicher spectral sequence and the existence of special Hermitian metrics on the manifold, such as balanced, SKT or generalized Gauduchon. The study of balanced metrics on nilmanifolds endowed with strongly non-nilpotent complex structures allows us to provide infinite families of compac

Pasquale Claudio Africa

Numerical simulations are ubiquitous in mathematics and computational science. Several industrial and clinical applications entail modeling complex multiphysics systems that evolve over a variety of spatial and temporal scales. This study introduces the design and capabilities of lifex, an open source C++ library for high performance finite element simulatio

Zuyan Chen, Adam Francis, Shuai Li, Bolin Liao

A novel meta-heuristic algorithm, Egret Swarm Optimization Algorithm (ESOA), is proposed in this paper, which is inspired by two egret species' (Great Egret and Snowy Egret) hunting behavior. ESOA consists of three primary components: Sit-And-Wait Strategy, Aggressive Strategy as well as Discriminant Conditions. The performance of ESOA on 36 benchmark functi

Vincent Meisner, Jonas von Wangenheim

Evidence suggests that participants in strategy-proof matching mechanisms play dominated strategies. To explain the data, we introduce expectation-based loss aversion into a school-choice setting and characterize choice-acclimating personal equilibria. We find that non-truthful preference submissions can be strictly optimal if and only if they are top-rank m

Triparna Mondal, Shashi C. L. Srivastava

We study the spectral properties of a multiparametric system having particle-hole symmetry in random matrix setting. We observe a crossover from Poisson to Wigner-Dyson like behavior in average local ratio of spacing within a spectrum of single matrix as a function of effective single parameter referred to as complexity parameter. The average local ratio of

Alessia Patuelli, Fabio Saracco

To achieve sustainable development worldwide, the United Nations set 17 Sustainable Development Goals (SDGs) for humanity to reach by 2030. Society is involved in the challenge, with firms playing a crucial role. Thus, a key question is to what extent firms engage with the SDGs. Efforts to map firms' contributions have mainly focused on analysing companies'

Dieuwertje Alblas, Christoph Brune, Kak Khee Yeung, Jelmer M. Wolterink

Personalised 3D vascular models are valuable for diagnosis, prognosis and treatment planning in patients with cardiovascular disease. Traditionally, such models have been constructed with explicit representations such as meshes and voxel masks, or implicit representations such as radial basis functions or atomic (tubular) shapes. Here, we propose to represen

Hiroto Shibuya, Takashi Toma

In this work, we investigate the effects of first-order phase transitions on the singlet fermionic dark matter in the scotogenic model. It is known that this dark matter candidate tends to conflict with the relevant constraints such as the neutrino oscillation data and charged lepton flavor violating processes if its thermal production mechanism is assumed.

Giorgos Livanas

We investigate Josephson junctions among conventional superconducting wires, in the presence of externally applied Zeeman fields and supercurrents. We demonstrate that the critical Josephson current and the current-phase relation of the junction depends on the relative orientation of the applied Zeeman fields and supercurrents. The controllability of the Jos

Max Tran

We give a brief critical examination of the special theory of relativity and a similar Newtonian framework to the first order of the $v/c$ ratio, focusing on the phenomena of aberration, Fresnel dragging, and the Doppler effect. We will show that both frameworks yield the same equations modeling these phenomena up to first order. We do this at a level unders

Václav Vávra, Dmytro Mishkin, Jiří Matas

We consider the problem of two-view matching under significant viewpoint changes with view synthesis. We propose two novel methods, minimizing the view synthesis overhead. The first one, named DenseAffNet, uses dense affine shapes estimates from AffNet, which allows it to partition the image, rectifying each partition with just a single affine map. The secon

G. J. Paz-Delgado, C. J. Pérez-del-Pulgar, M. Azkarate, F. Kirchner

This work presents a computationally lightweight motion planner for over-actuated platforms. For this purpose, a general state-space model for mobile platforms with several kinematic chains is defined, which considers non-linearities and constraints. The proposed motion planner is based on a sequential multi-stage approach that takes advantage of the warm st

Christian Fischer, Joachim Saur

Electromagnetic Star-Planet Interaction (SPI) describes the phenomenon, when a planet couples to its host star via electromagnetic forces. Alfv\'en waves can establish such a coupling by forming Alfv\'en wings. SPI allows phenomena that we do not know from the Solar System. Wing-wing interaction is such an example, where the Alfv\'en wings of two planets mer

Qingzhou Liu, Feng Wu

Multi-agent path finding (MAPF) is an active area in artificial intelligence, which has many real-world applications such as warehouse management, traffic control, robotics, etc. Recently, M* and its variants have greatly improved the ability to solve the MAPF problem. Although subdimensional expansion used in those approaches significantly decreases the dim

Bella Septina Ika Hartanti, Valentino Vito, Aniati Murni Arymurthy, Andie Setiyoko

Deforestation is one of the contributing factors to climate change. Climate change has a serious impact on human life, and it occurs due to emission of greenhouse gases, such as carbon dioxide, to the atmosphere. It is important to know the causes of deforestation for mitigation efforts, but there is a lack of data-driven research studies to predict these de

Chiman Qadir, Waleed Aziz, Ibrahim Hamad

In this paper the problems of integrable and linearizable Lotka-Volterra equations with $(\delta:-3 \delta:\delta)$-resonance are studied. The necessary conditions for both problems are obtained in the case when $\delta=1$ and it's sufficiency are proved. It is also shown that non-standard analysis has an important role in proving the sufficient integrable c

Kathryn E. Hare, Franklin Mendivil

In this paper, we determine the almost sure values of the $\Phi$-dimensions of random measures $\mu$ supported on random Moran sets in $\R^d$ that satisfy a uniform separation condition. This paper generalizes earlier work done on random measures on homogeneous Moran sets \cite{HM} to the case of unequal scaling factors. The $\Phi$-dimensions are intermediat

Benjamin Dufée, Bérenger Hug, Etienne Mémin, Gilles Tissot

A methodological framework for ensemble-based estimation and simulation of high dimensional dynamical systems such as the oceanic or atmospheric flows is proposed. To that end, the dynamical system is embedded in a family of reproducing kernel Hilbert spaces (RKHS) with kernel functions driven by the dynamics. In the RKHS family, the Koopman and Perron-Frobe

Leonid Mill, Oliver Aust, Jochen A. Ackermann, Philipp Burger

Artificial intelligence (AI), machine learning, and deep learning (DL) methods are becoming increasingly important in the field of biomedical image analysis. However, to exploit the full potential of such methods, a representative number of experimentally acquired images containing a significant number of manually annotated objects is needed as training data

Tao Wei, Zhengyu Tao, Xuejun Guo

We derive 10 new Ramanujan-Sato series of $1/\pi$ by using the method of Huber, Schultz and Ye. The levels of these series are 14, 15, 16, 20, 21, 22, 26, 35, 39.

L. D. Stanfield, A. W. Powell, S. A. R. Horsley, J. R. Sambles

We experimentally demonstrate a Purcell effect-based design technique for improved impedance matching, and thus enhanced radiation efficiency from a small microwave emitter. Using an iterative process centred on comparing the phase of the radiated field of the emitter in air with that of the emitter in a dielectric environment, we optimise the structure of a

Rahul Dhurkunde, Alexander H. Nitz

Current searches for gravitational waves from compact-binary objects are primarily designed to detect the dominant gravitational-wave mode and assume that the binary components have spins which are aligned with the orbital angular momentum. These choices lead to observational biases in the observed distribution of sources. Sources with significant spin-orbit

Dawei Zhai, Cong Chen, Cong Xiao, Wang Yao

Under time-reversal symmetry, a linear charge Hall response is usually deemed to be forbidden by the Onsager relation. In this work, we discover a scenario for realizing a time-reversal even linear charge Hall effect in a non-isolated two-dimensional crystal allowed by time reversal symmetry. The restriction by Onsager relation is lifted by interfacial coupl

Jialong Deng

In an attempt to develop higher-dimensional quasiconformal mappings on metric measure spaces with curvature conditions, i.e. from Ahlfors to Alexsandrov, we show that a non-collapsed $\mathrm{RCD}(0,n)$ space ($n\geq2$) with Euclidean growth volume is an $n$-Loewner space and satisfies the infinitesimal-to-global principle.

Callum W. Fairbairn, Roman R. Rafikov

Spiral density waves observed in protoplanetary discs have often been used to infer the presence of embedded planets. This inference relies both on simulations as well as the linear theory of planet-disc interaction developed for planets on circular orbits to predict the morphology of the density wake. In this work we develop and implement a linear framework

Jin Cheng, Firas Abi-Farraj, Farbod Farshidian, Marco Hutter

Model Predictive Control (MPC) schemes have proven their efficiency in controlling high degree-of-freedom (DoF) complex robotic systems. However, they come at a high computational cost and an update rate of about tens of hertz. This relatively slow update rate hinders the possibility of stable haptic teleoperation of such systems since the slow feedback loop

Victoriano Carmona, Fernando Fernández-Sánchez, Douglas D. Novaes

In this paper, we consider the family of planar piecewise linear differential systems with two zones separated by a straight line without sliding regions, that is, differential systems whose flow transversally crosses the switching line except for at most one point. In the research literature, many papers deal with the problem of determining the maximum numb

Van Phuc Bui, Trinh Van Chien, Eva Lagunas, Joël Grotz

Non-geostationary (Non-GSO) satellite constellations have emerged as a promising solution to enable ubiquitous high-speed low-latency broadband services by generating multiple spot-beams placed on the ground according to the user locations. However, there is an inherent trade-off between the number of active beams and the complexity of generating a large num

Stephen M. Barnett

It has often been remarked that single-photon interference experiments, however complicated, seem to behave very much in the same way as those performed in the classical regime, using the field generated by a laser. This observation has the status of being `well-known to those who know it', but perhaps mysterious to others. We discuss the reasons underlying

Xinyan Xie, Runxin Zhang, Yulin Shao, Lu Lu

Discovering sequences with desired properties has long been an interesting intellectual pursuit. In pulse compression radar (PCR), discovering phase codes with low aperiodic autocorrelations is essential for a good estimation performance. The design of phase code, however, is mathematically non-trivial as the aperiodic autocorrelation properties of a sequenc

Yangyang Liu, Zhen Chen, Chang Shu, Siou Chye Chew

The prosperous development of both hardware and algorithms for quantum computing (QC) potentially prompts a paradigm shift in scientific computing in various fields. As an increasingly active topic in QC, the variational quantum algorithm (VQA) leads a promising direction for solving partial differential equations on Noisy Intermediate Scale Quantum (NISQ) d

Farshid Khojasteh

The current research is devoted to find an affirmative answer to an open question related to $(s,r)-$contractive operators which have been introduced by Ovidiu Popescu.

Fangcheng Fu, Xupeng Miao, Jiawei Jiang, Huanran Xue

Vertical federated learning (VFL) is an emerging paradigm that allows different parties (e.g., organizations or enterprises) to collaboratively build machine learning models with privacy protection. In the training phase, VFL only exchanges the intermediate statistics, i.e., forward activations and backward derivatives, across parties to compute model gradie

Léo Jacqmin, Lina M. Rojas-Barahona, Benoit Favre

While communicating with a user, a task-oriented dialogue system has to track the user's needs at each turn according to the conversation history. This process called dialogue state tracking (DST) is crucial because it directly informs the downstream dialogue policy. DST has received a lot of interest in recent years with the text-to-text paradigm emerging a

Ozan Özdenizci, Robert Legenstein

Image restoration under adverse weather conditions has been of significant interest for various computer vision applications. Recent successful methods rely on the current progress in deep neural network architectural designs (e.g., with vision transformers). Motivated by the recent progress achieved with state-of-the-art conditional generative models, we pr

Malte Tölle, Ullrich Köthe, Florian André, Benjamin Meder

Differential privacy (DP) has arisen as the gold standard in protecting an individual's privacy in datasets by adding calibrated noise to each data sample. While the application to categorical data is straightforward, its usability in the context of images has been limited. Contrary to categorical data the meaning of an image is inherent in the spatial corre

Jay Aodh Mackenzie, Megan Jeanne Miller, Nicholas Hill, Mette Olufsen

Numerical simulations of real-world phenomena require a computational scheme and a computational domain. In the context of haemodynamics, the computational domain is the blood vessel network through which blood flows. Such networks contain millions of vessels that are joined in series and in parallel. It is computationally unfeasible to explicitly simulate b

Tobias A. de Jong, Luuk Visser, Johannes Jobst, Ruud M. Tromp

Terrace-sized, single-orientation graphene can be grown on top of a carbon buffer layer on silicon carbide by thermal decomposition. Despite its homogeneous appearance, a surprisingly large variation in electron transport properties is observed. Here, we employ Aberration-Corrected Low-Energy Electron Microscopy (AC-LEEM) to study a possible cause of this va

Matteo Cioni, Daniela Polino, Daniele Rapetti, Luca Pesce

Metals are traditionally considered hard matter. However, it is well known that their atomic lattices may become dynamic and undergo reconfigurations even well-below the melting temperature. The innate atomic dynamics of metals is directly related to their bulk and surface properties. Understanding their complex structural dynamics is thus important for many

Nikita O. Starodubcev, Nikolay O. Nikitin, Konstantin G. Gavaza, Elizaveta A. Andronova

In recent years generative design techniques have become firmly established in numerous applied fields, especially in engineering. These methods are demonstrating intensive growth owing to promising outlook. However, existing approaches are limited by the specificity of problem under consideration. In addition, they do not provide desired flexibility. In thi

Mee Seong Im, Venkat R. Dasari

Deep neural networks (DNN) have been widely used and play a major role in the field of computer vision and autonomous navigation. However, these DNNs are computationally complex and their deployment over resource-constrained platforms is difficult without additional optimizations and customization. In this manuscript, we describe an overview of DNN architect

Miltiadis Paschalis

We investigate the continuity and differentiability of the Hardy constant with respect to perturbations of the domain in the case where the problem involves the distance from a boundary submanifold. We also investigate the case where only the submanifold is deformed.

Souvik Das, Pralay Kumar Karmakar

A laboratory plasma-wall interaction-based astrophysical gravito-electrostatic sheath (GES) model is methodologically applied to study the dynamic stability of the magnetoactive bi-fluidic solar plasma system in the presence of turbulence effect. The spherically symmetric GES-model formalism couples the solar interior plasma (SIP, internally self-gravitating

Adil Bahaj, Safae Lhazmir, Mounir Ghogho

Knowledge Graph (KG) completion is an important task that greatly benefits knowledge discovery in many fields (e.g. biomedical research). In recent years, learning KG embeddings to perform this task has received considerable attention. Despite the success of KG embedding methods, they predominantly use negative sampling, resulting in increased computational

Tobias A. de Jong, Xingchen Chen, Johannes Jobst, Eugene E. Krasovskii

Stacking domain boundaries occur in Van der Waals heterostacks whenever there is a twist angle or lattice mismatch between subsequent layers. Not only can these domain boundaries host topological edge states, imaging them has been instrumental to determine local variations in twisted bilayer graphene. Here, we analyse the mechanisms causing stacking domain b

M. K. Tiwari, Arjun Singh, Ajay Khooha, U K Goutam

In Ayurveda, Lauha (Iron) bhasma is primarily used to cure diseases related with iron deficiency in humans. It is produced from purified raw metallic iron using a combination of multi-step traditional preparation processes described in the Ayurveda literature. Here, we present results of structural investigation performed on the medicinal grade Lauha bhasma

Barbara Grygiel, Konrad Patucha

The strongly correlated bosons in flat band systems are an excellent platform to study a wide range of quantum phenomena. Such systems can be realized in optical lattices filled with ultracold atomic gases. In this paper we study the Bose-Hubbard model in the Lieb lattice by means of the time-dependent Gutzwiller mean-field approach. We find that in the Mott

Christophe Reype, Radu S. Stoica, Antonin Richard, Madalina Deaconu

This paper presents a new interaction point process that integrates geological knowledge for the purpose of automatic sources detection of multiple sources in groundwaters from hydrochemical data. The observations are considered as spatial data, that is a point cloud in a multi-dimensional space of hydrogeochemical parameters. The key hypothesis of this appr

Niall Donlon, Romina Gaburro, Shari Moskow, Isaac Woods

We consider the issues of stability and reconstruction of the electrical anisotropic conductivity of biological tissues in a domain $\Omega\subset\mathbb{R}^3$ by means of the hybrid inverse problem of magneto-acoustic tomography with magnetic induction (MAT-MI). The class of anisotropic conductivities considered here is of type $\sigma(\cdot)=A(\cdot,\gamma

Steven Duplij

A generalization of the semisimplicity concept for polyadic algebraic structures is proposed. If semisimple structures can be presented in block diagonal matrix form (resulting in the Wedderburn decomposition), a general form of polyadic structures is given by block-shift matrices. We combine these forms to get a general shape of semisimple nonderived polyad

Ronika Sarkar, Arka Bandyopadhyay, Awadhesh Narayan

The interplay of topology and non-Hermiticity has led to diverse, exciting manifestations in a plethora of systems. In this work, we systematically investigate the role of non-Hermiticity in the Chern insulating Haldane model on a dice lattice. Due to the presence of a non-dispersive flat band, the dice-Haldane model hosts a topologically rich phase diagram

P. Fernandez de Cordoba, R. Gallego Torrome, S. Gavasso, J. M. Isidro

We regard the cosmological fluid within an exponentially expanding FLRW spacetime as the probability fluid of a nonrelativistic Schroedinger field. The scalar Schroedinger particle so described has a mass equal to the total (baryonic plus dark) matter content of the Universe. This procedure allows a description of the cosmological fluid by means of the opera

Jiaming Le, Yudan Su, Junying Ma, Long Cheng

The low-frequency collective excitations, which often occur in the terahertz or multi-terahertz spectral region, play an essential role in many novel emergent phenomena. Despite numerous studies in the bulk, detection of such excitations at interfaces remains challenging owing to the lack of feasible experimental techniques. Here, we show that interfacial lo

Gerlind Plonka, Yannick Riebe, Yurii Kolomoitsev

We analyze the structure of a one-dimensional deep ReLU neural network (ReLU DNN) in comparison to the model of continuous piecewise linear (CPL) spline functions with arbitrary knots. In particular, we give a recursive algorithm to transfer the parameter set determining the ReLU DNN into the parameter set of a CPL spline function. Using this representation,

Severin Bunk

Associated to each small category $C$, there is a category of $C$-shaped diagrams of simplicial sets and an $\infty$-category of $NC$-shaped homotopy coherent diagrams of spaces. We present a functor which exhibits the latter as the $\infty$-categorical localisation of the former at the objectwise weak homotopy equivalences. This builds on a Quillen equivale

Giulia Comini, Goeric Huybrechts, Manuel Sam Ribeiro, Adam Gabrys

The availability of data in expressive styles across languages is limited, and recording sessions are costly and time consuming. To overcome these issues, we demonstrate how to build low-resource, neural text-to-speech (TTS) voices with only 1 hour of conversational speech, when no other conversational data are available in the same language. Assuming the av

Winfried Lötzsch, Max Reimann, Martin Büssemeyer, Amir Semmo

Image-based artistic rendering can synthesize a variety of expressive styles using algorithmic image filtering. In contrast to deep learning-based methods, these heuristics-based filtering techniques can operate on high-resolution images, are interpretable, and can be parameterized according to various design aspects. However, adapting or extending these tec

Noel Merchán, José Angel Peláez, Elena de la Rosa

We consider the Hilbert-type operator defined by $$ H_{\omega}(f)(z)=\int_0^1 f(t)\left(\frac{1}{z}\int_0^z B^{\omega}_t(u)\,du\right)\,\omega(t)dt,$$ where $\{B^{\omega}_\zeta\}_{\zeta\in\mathbb{D}}$ are the reproducing kernels of the Bergman space $A^2_\omega$ induced by a radial weight $\omega$ in the unit disc $\mathbb{D}$. We prove that $H_{\omega}$ is

N. Schneider, V. Ossenkopf-Okada, S. Clarke, R. S. Klessen

We present N-PDFs of 29 Galactic regions obtained from Herschel imaging at high angular resolution, covering diffuse and quiescent clouds, and those showing low-, intermediate-, and high-mass star formation (SF), and characterize the cloud structure using the Delta-variance tool. The N-PDFs are double-log-normal at low column densities, and display one or tw

Venkatesh Vadde, Bhaskaran Muralidharan, Abhishek Sharma

We propose that a spin Hall effect driven magnetic tunnel junction device can be engineered to provide a continuous change in the resistance across it when injected with orthogonal spin currents. Using this concept, we develop a hybrid device-circuit simulation platform to design a network that realizes multiple functionalities of a convolutional neural netw

Felipe Cano, Nuria Corral, David Senovilla-Sanz

The analytic moduli of equisingular plane branches has the semimodule of differential values as the most relevant system of discrete invariants. Focusing in the case of cusps, the minimal system of generators of this semimodule is reached by the differential values attached to the differential $1$-forms of the so-called standard bases. We can complete a stan

Simon Briend, Francisco Calvillo, Gábor Lugosi

We study the problem of finding the root vertex in large growing networks. We prove that it is possible to construct confidence sets of size independent of the number of vertices in the network that contain the root vertex with high probability in various models of random networks. The models include uniform random recursive dags and uniform Cooper-Frieze ra

Stefano Bonzio, Andrea Loi

A Boolean algebra $\A$ equipped with a (finitely-additive) positive probability measure $m$ can be turned into a metric space $(\A , d_{m})$, where $d_{m}(a,b)= m ((a\wedge\neg b)\vee(\neg a\wedge b))$, for any $a,b\in A$, sometimes referred to as \emph{metric Boolean algebra}. In this paper, we study under which conditions the space of atoms of a finite met

Stevo Todorcevic, Konstantinos Tyros

We prove a dualization of the Graham--Rothschild Theorem for variable words indexed by homogeneous trees.

Tom Kimpson, E. Adam Paxton, Matthew Chantry, Tim Palmer

Reduced precision floating point arithmetic is now routinely deployed in numerical weather forecasting over short timescales. However the applicability of these reduced precision techniques to longer timescale climate simulations - especially those which seek to describe a dynamical, changing climate - remains unclear. We investigate this question by deployi

Alexander Ochirov, Evgeny Skvortsov

We propose a new, chiral description for massive higher-spin particles in four spacetime dimensions, which facilitates the introduction of consistent interactions. As proof of concept, we formulate three theories, in which higher-spin matter is coupled to electrodynamics, non-Abelian gauge theory or gravity. The theories are chiral and have simple Lagrangian

Jing Tan, Ramin Khalili, Holger Karl, Artur Hecker

We formulate offloading of computational tasks from a dynamic group of mobile agents (e.g., cars) as decentralized decision making among autonomous agents. We design an interaction mechanism that incentivizes such agents to align private and system goals by balancing between competition and cooperation. In the static case, the mechanism provably has Nash equ

Mathieu Lizée, Matthias Stosiek, Christophe Brun, Igor Burmistrov

The interplay of superconductivity and disorder generates a wealth of complex phenomena. In particular, the peculiar structure of diffusive electronic wavefunctions is predicted to increase the superconducting critical temperature in some range of disorder. In this work, we use an epitaxial monolayer of lead showing a simple band structure and homogenous str

Tegg Taekyong Sung, Bo Ryu

Neural schedulers based on deep reinforcement learning (DRL) have shown considerable potential for solving real-world resource allocation problems, as they have demonstrated significant performance gain in the domain of cluster computing. In this paper, we investigate the feasibility of neural schedulers for the domain of System-on-Chip (SoC) resource alloca

R. F. Lebed, T. Skwarnicki, L. An, S. Dobbs

Hadron spectroscopy, the driving force of high-energy physics in its early decades, has experienced a renaissance in interest over the past 20 years due to the discovery of scores of new, potentially "exotic states" (tetraquarks, pentaquarks, hybrid mesons, glueballs), as well as the observation of many new "conventional" hadrons. The new discoveries expose

Yucheol Jung, Wonjong Jang, Soongjin Kim, Jiaolong Yang

A 3D caricature is an exaggerated 3D depiction of a human face. The goal of this paper is to model the variations of 3D caricatures in a compact parameter space so that we can provide a useful data-driven toolkit for handling 3D caricature deformations. To achieve the goal, we propose an MLP-based framework for building a deformable surface model, which take

Robert Susik, Robert Nowotniak

Blockchain received a vast amount of attention in recent years and is still growing. The second generation of blockchain, such as Ethereum, allows execution of almost any program in Ethereum Virtual Machine (EVM), making it a global protocol for distributed applications. The code deployment and each operation performed in EVM cost the network fee called gas,

M. Sambataro, N. Sandulescu

The band structure of N=Z nuclei is constructed from intrinsic states defined in terms of quartets. The simplest of these states is a condensate of collective quartets with isospin T=0. The other intrinsic states are built by promoting one quartet of the condensate to an excited T=0 configuration. From these intrinsic states, by angular momentum projection,

Walter Bridges, Johann Franke, Joshua Males

Recent work of Cesana, Craig and the third author shows that the trace of plane partitions is asymptotically equidistributed in residue classes mod $b$. Applying a technique of the first two authors and Garnowski, we prove asymptotic formulas for the secondary terms in this equidistribution, which are controlled by certain complex numbers generated by a twis